Quick method for estimating the margin of error



Quick method for estimating the margin of error

[pic]

Use the sample proportion p from a simple random sample of size n to estimate an unknown population proportion p. The margin of error for 95% confidence is roughly equal to . [pic]

What is the margin of error?

We would like to find out what proportion of adults in the U. S. voted in the last election.

This proportion is called a parameter describing the adult population of the U. S. However we don’t know what this proportion is. And short of asking each adult we won’t know.

But one way of estimating this number is to take a poll of a sample of adults.

In our poll 1700 people were selected “at random” and asked if they voted in the last election. 795 said yes. So for our sample

p = [pic] [pic] .468 or roughly 47%[pic]

So we could estimate that 47% of the adult population voted in the last election. We would like to say something about how confident we are that our estimate is correct. From the above estimate, we

could say that margin of error for 95% confidence is about [pic] or roughly 0.024 or 2.4%

Confidence Statements

For the above survey we would say something like:

Our poll found that 47% of adults in the U.S. voted in the last election. We are 95% confident that the poll is correct with a margin of error of 2.4%. Or We are 95% confident that between 44.6% and 49.4% of the adults voted in the last election.

A confidence statement has two parts: a margin of error and a level of confidence. The margin of error says how close the sample statistic lies to the population parameter. The level of confidence says what percent of all possible samples satisfy the margin of error. A confidence statement is a fact about what happens in all possible samples, used to say how much we can trust the result of one sample. "95% confidence" means "We used a sampling method that gives a result this close to the truth 95% of the time." Here are some hints for interpreting confidence statements:

The conclusion of a confidence statement always applies to the population, not to the sample. We know exactly how the 1700 people in the sample acted, because we interviewed them. The confidence statement uses the sample result to say something about the population of all adults.

Our conclusion about the population is never completely certain. Gallup's sample might be one of the 5% that miss by more than 2.4 percentage points.

A sample survey can choose to use a confidence level other than 95%. We pay for higher confidence with a larger margin of error. For the same sample, a 99% confidence statement requires a larger margin of error than 95% confidence. If you are content with 90% confidence, you get in return a smaller margin of error. Remember that our quick method only gives the margin of error for 95% confidence.

It is usual to report the margin of error for 95% confidence. If a news report gives a margin of error but leaves out the confidence level, it's pretty safe to assume 95% confidence.

Want a smaller margin of error with the same confidence? Take a larger sample. Remember that larger samples have less variability. You can get as small a margin of error as you want and still have high confidence by paying for a large enough sample.

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